Assessing the Local Mechanical Environment in Medial Opening Wedge High Tibial Osteotomy Using Finite Element Analysis
Bibliographic record
Abstract
High-tibial osteotomy (HTO) is a surgical technique aimed at shifting load away from one tibiofemoral compartment, in order the reduce pain and progression of osteoarthritis (OA). Various implants have been designed to stabilize the osteotomy and previous studies have been focused on determining primary stability (a global measure) that these designs provide. It has been shown that the local mechanical environment, characterized by bone strains and segment micromotion, is important in understanding healing and these data are not currently available. Finite element (FE) modeling was utilized to assess the local mechanical environment provided by three different fixation plate designs: short plate with spacer, long plate with spacer and long plate without spacer. Image-based FE models of the knee were constructed from healthy individuals (N = 5) with normal knee alignment. An HTO gap was virtually added without changing the knee alignment and HTO implants were inserted. Subsequently, the local mechanical environment, defined by bone compressive strain and wedge micromotion, was assessed. Furthermore, implant stresses were calculated. Values were computed under vertical compression in zero-degree knee extension with loads set at 1 and 2 times the subject-specific body weight (1 BW, 2 BW). All studied HTO implant designs provide an environment for successful healing at 1 BW and 2 BW loading. Implant von Mises stresses (99th percentile) were below 60 MPa in all experiments, below the material yield strength and significantly lower in long spacer plates. Volume fraction of high compressive strain ( > 3000 microstrain) was below 5% in all experiments and no significant difference between implants was detected. Maximum vertical micromotion between bone segments was below 200 μm in all experiments and significantly larger in the implant without a tooth. Differences between plate designs generally became apparent only at 2 BW loading. Results suggest that with compressive loading of 2 BW, long spacer plates experience the lowest implant stresses, and spacer plates (long or short) result in smaller wedge micromotion, potentially beneficial for healing. Values are sensitive to subject bone geometry, highlighting the need for subject-specific modeling. This study demonstrates the benefits of using image-based FE modeling and bone theory to fine-tune HTO implant design.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".